A legal document, such as a court judgment or orders received from judicial authorities, is a complex document which contains a large volume of text. A judgment includes text describing a court's judicial opinion for a legal case and also includes citations of other legal cases for establishing precedence for the decision. To aid readers in quickly scanning the judgment and identifying key legal points of the judgment, a headnote is provided preceding the judicial opinion in the legal document. The headnote is a brief summary of the judicial opinion in the legal judgment which aids readers to locate discussion of a legal issue in the judicial opinion. The headnote is typically prepared by a human editor by reading the entire judgment and extracting portions of text manually which are relevant to be added to the headnote.
However, analyzing legal documents and identifying key legal points to prepare headnotes for the legal documents manually is a complex and time consuming task because of the volume of text in such documents. As such, there is a growing need for an automated process for extracting headnotes efficiently and accurately in legal documents. Generally, automated systems exist that are used to extract entities such as ‘names of places’ and ‘names of companies’ from text or are used to categorize documents into pre-determined categories. However, the existing systems do not process unstructured information from text which is relevant for inclusion in headnotes. For headnote preparation, these systems do not efficiently and accurately recognize portions of text in the legal document that represent legal reasoning and analysis on a point of law.
In light of the above, there is a need for a method and system that automatically analyzes the huge text in the legal documents and extracts text in the legal document which can be appended in the headnote. Further, there is a need for a method and system that renders the legal document on a display screen of an editor by tagging and highlighting portions of text which has the highest probability to be a headnote. Also, there is a need for a method and system that extracts headnotes from legal documents in a manner which enables the editor to interpret the tagged portions of text as headnotes accurately. In addition, there is a need for a method and system that minimizes the time consumed in extracting headnotes from legal documents.